5 Strategy
Scenario 1. If an organization so far has applied an exclusive market-oriented strategy, then external determinants such as customers’ demands, the organiza-
5.3 Success factors, barriers and risks
5.3.4 Management of knowledge risks
edge transfer between the partner organizations. An attempt to transfer knowl- edge that cannot be carried out sufficiently supposedly can be caused by too rigid rules for knowledge transfer, also called overprotection, but also by vague rules. The latter leave employees hesitant about freely sharing knowledge because they are not aware what is expected from them and what would be con- sidered an act against the interests of the organization. This can result in a lack of the required knowledge assets.
4. Loss of knowledge assets is unrecoverable and also leads to a lack at the level of operational business processes. Examples are fluctuation of employees with unique knowledge, skills, social networks or experiences to other jobs within the organization (intra-fluctuation), to other organizations (inter-fluctuation) or due to their retirement (extra-fluctuation), non-documentation of knowledge, dele- tion of documented knowledge or malfunctioning of IT infrastructures including backup services239.
5. Diffusion means access to sensitive or competitive knowledge by non-autho- rized persons. Contrary to knowledge loss, diffusion means that knowledge is still available, but not exclusively to the organization. Some authors stress this risk and the possibly resulting dilution of competitive advantages, especially in inter-organizational settings as strategic alliances, clusters, joint ventures, (vir- tual) networks and professional communities240. Examples for knowledge diffu- sion risks are access to unauthorized persons, social or reverse engineering, loss or theft of unsecured, especially mobile devices with replicated documented knowledge or unsecured access to IT infrastructures.
Causes are not isolated from each other, but can also interact. For example, fluc- tuation of employees on the one hand leads to knowledge loss for processes, rou- tines and practices in which the employees participated. On the other hand, fluctua- tion bears risks that knowledge diffuses and its exclusivity is lost by re-applying firm-specific knowledge at a competing organization (Matusik/Hill 1998, 687).
Assessment. Identified knowledge risks have to be assessed concerning their prob- ability and severity of the resulting losses. This assessment has to be based on the value of the knowledge assets and also interactions between knowledge assets have to be considered. However, the valuation of knowledge assets is still in its infancy and consequently the assessment of knowledge risks is still challenging242. Control. Governance measures have to be selected to control knowledge risks.
Governance means the set of processes and policies affecting the way handling of knowledge is directed, administered or controlled (Zyngier et al. 2006, 3). Exam- ples are using intellectual property rights, measures to reduce dependencies, reten- tion planning for leaving employees, organizational conception of access rights and their technical implementation and maintenance as well as insurance policies.
Evaluation. Finally, treatment of knowledge risks is an ongoing process since risks, probabilities, severity as well as the efficiency of governance measures change over time.
FIGURE B-19. Knowledge risk management process
Due to its importance, the control step is illustrated in the following with the help of the example of governance of knowledge transfer, particularly showing the trade-off that has to be made between intentional and unintentional knowledge transfer (Bayer/Maier 2006).
242. See chapter 8 - “Economics” on page 395.
object social system
person
identification assessment
control evaluation
Knowledge transfer can be classified into organization-internal and -external transfer. From a risk perspective, external knowledge transfer is of primary interest and is initiated intentionally or unintentionally by the source, happens by chance or is initiated on purpose by the recipient (Kogut/Zander 1992, 384, Teece 2000, 134). Success of the transfer can be determined e.g., by the extent to which the source’s knowledge is recreated at the recipient’s end (Cummings/Teng 2003, 41).
Intention refers to the macro-level and is considered as the intention of the orga- nization. However, knowledge transfer can also be intended by an individual employee as sender on the micro-level, but not by the organization. Such conflicts can be the consequence of e.g., lack of awareness concerning the value of trans- ferred knowledge or employees’ opportunistic behavior.
Risks concerning knowledge transfer in (knowledge) cooperations are primarily focused on the level of operative business processes since particularly middle man- agers and engineers interact in day-to-day business with their counterparts (Baughn et al. 1997, 104). Intended and balanced reciprocal knowledge transfer is condu- cive to stability of alliances (Escribá-Esteve/Urra-Urbieta 2002, 340f).
The risk of insufficient or imbalanced intended as well as unintended knowledge transfer243 in alliances depends on a number of characteristics that can be struc- tured into (1) source and recipient, (2) transferred knowledge and (3) context in which knowledge transfer occurs (see Figure B-20).
FIGURE B-20. Characteristics influencing knowledge transfer244
(1) Characteristics of source and recipient include e.g., the source’s capability to explicate knowledge, the source’s reliability, the receiver’s absorptive capacity,
243. For the empirical study which is briefly sketched out in section 5.3.5 - “Empirical study: KnowRisk” on page 146, unintended knowledge transfer was reconceptualized as knowledge diffusion.
244. Source: Bayer/Maier 2006.
governance of knowledge risks
intended knowledge transfer
unintended knowledge transfer characteristics of
source / recipient characteristics of knowledge
characteristics of context:
- relationship - compatibility - infrastructure - protective measures
i.e. acquisition, assimilation, transformation and exploitation of knowledge, as well as the motivation of both partners245. High values of these characteristics posi- tively influence both, intended and unintended knowledge transfer.
(2) Characteristics of knowledge comprise e.g., its ambiguity, specificity, com- plexity, dependency on other knowledge and tacitness246. The more these charac- teristics apply to the transferred knowledge, the more difficult it is to realize a suc- cessful replication at the recipient’s side. This means that risk of unintended knowledge transfer decreases and risk of insufficient intended knowledge transfer increases with these characteristics.
(3) Characteristics of the context in which knowledge transfer occurs can be subdivided into the four categories relationship, compatibility, infrastructure and protective measures. These are focussed by governance measures since they are subject to influences by organizational routines and practices whereas the other characteristics are either domain- and knowledge-specific or are dependent on the involved individuals which cannot be directly influenced. For each of the four cat- egories, factors influencing knowledge transfer that have been found in the litera- ture are discussed. The factors are structured according to their impact on intended versus unintended knowledge transfer and to what consequences they bear for set- ting up governance rules in Table B-7 and are emphasized in Italic in the text.
245. Lei 1993, 36, Szulanski 1996, 31, Zahra/George 2002, 189f.
246. Matusik/Hill 1998, 687, Simonin 1999, 598ff.
TABLE B-7. Potential effects of factors influencing knowledge transfer risks
factor intended
knowledge transfer
unintended knowl-
edge transfer governance of knowl- edge risk joint negative influence
organizational distance - - < / !
cultural distance - - < / !
knowledge distance - - < / !
joint positive influence
physical closeness + + > / !
collaborative use of informa- tion systems
+ + > / !
number of channels for inter- action
+ + > / !
boundary spanners + + > / !
negative-positive influence
competition - + <
Relationship. The simultaneous occurrence of cooperation and competition in an alliance has been described as co-opetition247. Thus, the partnership is influenced by the level of competition, i.e. by similarity of the business line, overlapping prod- ucts and customers as well as the partners’ learning intents that can range from mere access to internalization of knowledge248. Partners differ how aggressively they want to realize these intents and behave eventually opportunistically with an intent to “outlearn” the partner249. Opportunistic behavior presumes as precondi- tions possession of privileged information, opportunity and motive (Davies 2001, 45ff). The importance of reputation in the considered industry reduces the risk of opportunistic behavior of the partner by limiting opportunity (Gulati et al. 2000, 209).
Relational capital or trust is built over a long period of time and positively influ- ences willingness to share knowledge250 and mutuality of the transfer. If trust exists, one can expect that transferred knowledge is not exploited by the partner (Kale et al. 2000, 222). Low competition, low intents to outlearn and high level of trust positively influence intended knowledge transfer and reduce the probability of exploitation of unintended knowledge transfer.
Compatibility. Differences between e.g., institutions, business practices and orga- nizational culture cause organizational distance251. Cultural distance, i.e. cultural differences concerning language, cultural norms or practices, is particularly rele- vant for international alliances252. Knowledge distance, i.e. differences of the part-
intent to outlearn - + <
opportunistic behavior - + <
trust + - >
negative-indifferent influence
transfer policies +/- - !
information security policies +/- - !
inter-organizational agree- ments
+/- - !
gatekeepers +/- - !
intellectual property rights +/- - !
247. Brandenburger/Nalebuff 1998, 11-39, Dowling/Lechner 1998.
248. Hamel 1991, 90f, Baughn et al. 1997, 106, Mohr/Sengupta 2002, 291ff.
249. Hamel et al. 1989, 134, Lei 1993, 36.
250. See section 6.4.2 - “Willingness to share knowledge” on page 223.
251. Simonin 1999, 603, Szulanski et al. 2003, 144f.
TABLE B-7. Potential effects of factors influencing knowledge transfer risks
factor intended
knowledge transfer
unintended knowl-
edge transfer governance of knowl- edge risk
ners’ knowledge bases influence expected success of knowledge transfer by hin- dering re-contextualization253. The more similar the partners, the easier knowledge can be transferred.
Infrastructure. Physical closeness of partners can be the result of e.g., geographi- cal proximity of facilities, joint production or rotation of employees. This posi- tively affects knowledge transfer by increasing probability of face-to-face meet- ings, observability and transparency254. Collaborative use of information systems can support intended knowledge transfer, but can also be accompanied by lack of access control and other security risks that increase the probability of unintended knowledge transfer (Schmaltz et al. 2004, 3f). Subject to defined security require- ments, organizations can control risks e.g., by substituting systems or enhancing the security level of systems that do not comply with the requirements. The number of channels for interaction increases knowledge transfer, but reduces control and thus increases probability of unintended knowledge transfer (Hamel et al. 1989, 136). Finally, boundary objects, i.e. physical objects, technologies or techniques shared by communities, and boundary spanners as organizational roles can improve knowledge transfer by promoting development of shared understand- ing255.
Protective measures. Transfer policies materialize intentions of organizations and determine which knowledge can be handed on to partners. For example, classifica- tion mitigates unintended knowledge transfer while over-classification hinders intended knowledge transfer256. This solves the problem that employees retain knowledge that should be transferred or transfer it too generously since they do not know whether knowledge may, should or even must be transferred or not. Informa- tion security policies determine what behavior is expected from employees when using enterprise assets and what unwanted effects noncompliance can cause (Pelt- ier 2005, 39). Inter-organizational agreements determine e.g., in which areas knowledge is transferred and how transfer occurs (Loebbecke et al. 1999, 20). Such agreements can also regulate to what extent knowledge can be used beyond the alliance. The latter prevents the risk of knowledge spillovers since knowledge could be transferred by a multi-stage process to direct competitors (Erickson/Roth- berg 2005, 11). Gatekeepers as organizational roles can control external knowl- edge transfer and reduce the probability of unintended knowledge transfer257, but can also negatively affect intended knowledge transfer. Finally, intellectual prop- erty rights can limit use of transferred knowledge beyond the alliance, whereas these rights are still only fragmentary compared to property rights for tangible assets258.
252. Simonin 1999, 602, Lane et al. 2001, 1143f.
253. Hamel 1991, 91, Cummings/Teng 2003, 46f.
254. Loebbecke et al. 1999, 35ff, Cummings/Teng 2003, 46.
255. Awazu 2004, 18f.
256. Hamel et al. 1989, 138, Desouza/Vanapalli 2005, 80.
257. Hamel et al. 1989, 136, Awazu 2004, 19.
Table B-7 summarizes these influences. The symbol (+) means that the factor is positively correlated with probability of successful re-contextualization, frequency and mutuality of intended knowledge transfer or probability and frequency of unin- tended knowledge transfer respectively. The symbol (-) represents the opposite.
The symbol (+/-) means that it is undetermined how the factors affect knowledge transfer. Each factor is assigned to one of four categories according to the direc- tions of the influences. The last column shows implications for setting up gover- nance rules for managing knowledge risks. The symbol (>) suggests to strengthen the corresponding factor whereas the symbol (<) suggests the opposite. In the case of the symbol (!) the factors require weighing and corrective measures must be taken because it is undetermined what consequences increasing or decreasing the factors would have.
The expected influences of the factors suggest varying strategies for setting gov- ernance rules for knowledge risks. However, rules that reduce risks of unintended knowledge transfer rarely simultaneously enhance intended knowledge transfer.
Thus, organizations have to weigh potential gains of external knowledge transfer with potential losses and select their measures accordingly. Generally, organiza- tions supposedly either risk low intended and unintended knowledge transfer by limiting transfer too much or risk depreciating knowledge assets by transferring too generously. In order to avoid erosion of the market position, knowledge assets have to be restricted in a balanced way.
Heuristics are needed concerning rules governing knowledge risks. While com- piling this book, the author leads an empirical study described in the following sec- tion 5.3.5 on the basis of which an instrument can be developed that helps organi- zations to assess, weigh and prioritize factors influencing knowledge risks and select appropriate measures of governance.